Image enhancement method for digital mammography

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Purpose: To evaluate in clinical use a practical iterative deconvolution method to enhance contrast and image resolution in digital breast tomosynthesis. A novel rapidly converging, iterative deconvolution algorithm for improving the quantitative accuracy of previously reconstructed breast images by commercial breast tomosynthesis system is demonstrated. Materials and Methods: The method was tested on phantoms and clinical breast imaging data. Data acquisition was performed on a commercial Hologic Selenia Dimensions digital breast tomosynthesis system. The method was applied to patient breast images previously processed with Hologic Selenia conventional and C-View software to determine improvements in resolution and contrast to noise ratio. Results: In all of the phantom and patients' breast studies the post-processed images proved to have higher resolution and contrast as compared with images reconstructed by Hologic methods. In general, the values of CNR reached a plateau at around 8 iterations with an average improvement factor of about 1.8 for processed Hologic Selenia images. Improvements in image resolution after the application of the method are also demonstrated. Conclusions: A rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach that operates on patient DICOM images has been used for quantitative improvement in digital breast tomosynthesis. The method can be applied to clinical breast images to improve image quality to diagnostically acceptable levels and will be crucial in order to facilitate diagnosis of tumor progression at the earliest stages. The method can be considered as an extended blind deblurring (or Richardson-Lucy like) algorithm with multiple resolution levels.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2018
Subtitle of host publicationImage Processing
PublisherSPIE
Volume10574
ISBN (Electronic)9781510616370
DOIs
StatePublished - Jan 1 2018
EventMedical Imaging 2018: Image Processing - Houston, United States
Duration: Feb 11 2018Feb 13 2018

Other

OtherMedical Imaging 2018: Image Processing
CountryUnited States
CityHouston
Period2/11/182/13/18

Keywords

  • digital breast tomosynthesis
  • image contrast and resolution improvement
  • quantitative breast cancer image enhancement
  • resolution subsets-based iterative method

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Slavine, N. V., Seiler, S., Blackburn, T. J., & Lenkinski, R. E. (2018). Image enhancement method for digital mammography. In Medical Imaging 2018: Image Processing (Vol. 10574). [105740G] SPIE. https://doi.org/10.1117/12.2293604